1. Field of the Invention
This invention relates generally to the field of classifying and querying a database of images.
2. Description of the Related Art
Huge amounts of information are being circulated daily at an uninterrupted pace on the World-Wide Web (WWW). Additionally, in museums and photo stock agencies, millions of images are stored for on-line usage. With the explosive growth in the volume and distribution of information, more intelligent information processing and management has become critical. Various methods of accessing target data have been developed to address issues relating to image retrieval, image clustering, query interface and WWW information retrieval.
Several experimental image-clustering systems have also been proposed. In K. Hirata, et al, "The Concept of Media-based Navigation and Its Implementation on Hypermedia System `Miyabi`," NEC Research & Development, Vol.35, No. 4, pp. 410-420, October 1994, the present inventor has focused on color information. Color values are extracted from the image and are mapped on to hue, lightness and saturation (HLS) color spaces. Based on the results, users can access an images directory or filter out the images for searching.
A. Del Bimbo, et al, "Shape Indexing by Structural Properties," International Conference on Multimedia Computing and Systems, pp.370-377, June, 1997 focuses on clustering based upon shape similarity. Based on a multi-scale analysis, Del Bimbo et al. have attempted to extract the hierarchical structure of shape. Using this hierarchical structure, Del Bimbo et al. have tried to provide effective search capabilities. While this method is based on the boundary analysis, it assumes that boundary is extracted correctly. However, this is not always the case, since images extracted from the Web usually include so many elements, thus, making it difficult to extract individual objects. Del Bimbo et al. does not describe a way to solve this problem.
Image indexing using feature vectors is based on moment invariant (See, e.g., Flickner et al, "Query by Image and Video Content: The QBIC System," Intelligent Multimedia Information Retrieval, edited by Mark T. Maybury, Chapter 1, Reprinted from IEEE Computer, 28(9): 23-31, September, 1995), or on boundary features (See R. Mehrotra et al, "Similar-Shape Retrieval in Shape Data Management," IEEE Computer, pp. 57-62, September 1995). Such image indexing also assumes the correct extraction of the object (or input by a user). This method is very hard to apply directly to large-scale image systems, such as the WWW, requiring automatic classification.
C. Carson, et al, "Color- and Texture-Based Image Segmentation Using EM and Its Application to Image Querying and Classification," IEEE Transaction on Pattern Analysis and Machine Intelligence, in review (http://www.cs.berkeley.edu/.about.carson/papers/pami.html), extracts objects from images based on color and texture. Using the combination of extracted objects and their attributes (top two colors and texture), Carson et al. tries to categorize images into several groups. Shape or positional information is not considered.